Multi-attribute group three-way decision making with degree-based linguistic term sets

Abstract

When using several possible linguistic terms with different weights (represented by probability values) to express preferences, the probability distribution of those linguistic terms is usually hard to be obtained. In this paper, we utilize degree values to reflect the weights of possible linguistic terms and first propose a novel concept called degree-based linguistic term set (DLTS) from the perspective of degree. Then we present a new multi-attribute three-way decision method under the environment of DLTSs. Furthermore, considering that if only one person is involved in decision-making process, it may produce unreasonable or unfair evaluation results. We choose multiple decision-makers to participate in the decision-making process, and propose a multi-attribute group three-way decision method by utilizing the idea of TOPSIS method under the environment of DLTSs. Since the weights of multiple decision-makers (DMs) may be different, we give a method to determine the weights by using the idea of information gain based on the three-way decision results of each decision-maker (DM). Finally, we compare our decision method with an existing decision method, and illustrate the effectiveness of our method through a concrete example.